Steganography,the art of concealing information within innocuous mediums,has been practiced for centuries and continues to evolve with advances in digital technology.In the modern era,steganography has become an essen...Steganography,the art of concealing information within innocuous mediums,has been practiced for centuries and continues to evolve with advances in digital technology.In the modern era,steganography has become an essential complementary tool to cryptography,offering an additional layer of security,stealth,and deniability in digital communications.With the rise of cyber threats such as hacking,malware,and phishing,it is crucial to adopt methods that protect the confidentiality and integrity of data.This review focuses specifically on text-in-image steganography,exploring a range of techniques,including Least Significant Bit(LSB),Pixel Value Differencing(PVD),and Transform Domain methods,to evaluate their effectiveness in real-world applications.The analysis covers key parameters such as embedding capacity,computational complexity,and the interplay with data compression and cryptographic techniques.While significant progress has been made in improving the security and quality of images in steganographic systems,challenges remain.For instance,higher payloads can lead to reduced Peak Signal-to-NoiseRatio(PSNR),compromising image quality.Despite these limitations,recent advancements show promising results in balancing security with minimal distortion.This paper provides valuable insights into the strengths and weaknesses of current techniques,highlighting future research directions that may enhance both the robustness and efficiency of steganographic methods in digital security.展开更多
Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deplo...Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.展开更多
Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate w...Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation systems.VANETs steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection.This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss.According to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network conditions.In this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and filtering.This study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.展开更多
The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a...The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.展开更多
Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these ...Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload.A coverless data hiding concept is proposed to solve this issue.Coverless does not mean that cover is not required,or the payload can be transmitted without a cover.Instead,the payload is embedded by cover generation or a secret message mapping between the cover file and the payload.In this paper,a new coverless image steganography method has been proposed based on the jigsaw puzzle image generation driven by a secret message.Firstly,the image is divided into equal rows then further divided into equal columns,creating blocks(i.e.,sub-images).Then,according to secret message bits and a proposed mapping function,each block will have tabs/blanks to get the shape of a puzzle piece creating a fully shaped jigsaw puzzle stego-image.After that,the generated jigsaw puzzle image is sent to the receiver.Experimental results and analysis show a good performance in the hiding capacity,security,and robustness compared with existing coverless image steganography methods.展开更多
Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication w...Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time.Practically,AI techniques can be utilized to design image steganographic techniques in IIoT.In addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access.In order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT environment.The proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover image.In addition,the multi-level discrete wavelet transform(DWT)based transformation process takes place.Besides,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic System.At last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover image.In order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different measures.The experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.展开更多
Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.T...Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.The confidentiality,integrity,and availability of the data are at risk because of the emerging technologies and complexity in software applications,and therefore,there is a need to secure such systems and data.There are various methodologies to deal with security issues when utilizing an open system like the Internet.This research proposes a new technique in steganography within RGB shading space to achieve enhanced security compared with existing systems.We evaluate our approach with the help of diverse image quality evaluation techniques including MSE(Mean Square Error),RMSE(Root Mean Square Error),PSNR(Peak Signal-to-Noise Ratio),MAE(Mean Absolute Error),NCC(Normalized Cross-Correlation)and SSIM(Structural Similarity Index).Our experimental results demonstrate improved strength,intangibility,and security when contrasted with existing techniques and vindicate the effectiveness of this exploration work.The proposed approach achieved a 3.6701%average higher score for PSNR Correlation than the next best existing approach.Moreover,in PSNR with a variable amount of cipher embedded in the same images of the same dimensions,the proposed approach attained a 5.22%better score.Embedding the same size of cipher in images of different size resulted a 3.56%better score.展开更多
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a s...Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.展开更多
In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this pape...In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection.For the spatial image,this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain.Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography,and use the minimum distortion coding to realize the embedding of the secret messages.Finally,according to the embedding modification amplitude of secret messages in the new embedded domain,the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain.The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation,the bilinear interpolation and the bicubic interpolation.And the average correct extraction rate of embedded messages increases from 50%to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method,compared with the classical steganography algorithm S-UNIWARD.Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.展开更多
Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system.This paper presents an image scrambling method that is very ...Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system.This paper presents an image scrambling method that is very useful for grayscale secret images.In this method,the secret image decomposes in three parts based on the pixel’s threshold value.The division of the color image into three parts is very easy based on the color channel but in the grayscale image,it is difficult to implement.The proposed image scrambling method is implemented in image steganography using discrete wavelet transform(DWT),singular value decomposition(SVD),and sorting function.There is no visual difference between the stego image and the cover image.The extracted secret image is also similar to the original secret image.The proposed algorithm outcome is compared with the existed image steganography techniques.The comparative results show the strength of the proposed technique.展开更多
Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into ...Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.展开更多
Internet brings us not only the convenience of communication but also some security risks,such as intercepting information and stealing information.Therefore,some important information needs to be hidden during commun...Internet brings us not only the convenience of communication but also some security risks,such as intercepting information and stealing information.Therefore,some important information needs to be hidden during communication.Steganography is the most common information hiding technology.This paper provides a literature review on digital image steganography.The existing steganography algorithms are classified into traditional algorithms and deep learning-based algorithms.Moreover,their advantages and weaknesses are pointed out.Finally,further research directions are discussed.展开更多
The trend of digital information transformation has become a topic of interest.Many data are threatening;thus,protecting such data from attackers is considered an essential process.Recently,a new methodology for data ...The trend of digital information transformation has become a topic of interest.Many data are threatening;thus,protecting such data from attackers is considered an essential process.Recently,a new methodology for data concealing has been suggested by researchers called coverless steganography.Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image.This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems.The system uses the secret message to generate the stego image in the form of one of the Intelligence Quotient(IQ)games,the maze.Firstly,a full grid is generated with several specific rows and columns determined from the number of bits of the secret message.Then,these bits are fed to the full grid to form the maze game stego image.Finally,the generated maze game stego image is sent to the recipient.The experimental results,using the Bit Error Rate(BER),were conducted,and confirmed the strength of this system represented by a high capacity,perfect performance,robustness,and stronger hiding system compared with existing coverless steganography systems.展开更多
Steganography is the art of hiding a secret message in some kind of media. The main goal is not to hide only the secret message but also the existence of communication and secure data transferring. There are a lot of ...Steganography is the art of hiding a secret message in some kind of media. The main goal is not to hide only the secret message but also the existence of communication and secure data transferring. There are a lot of methods that were utilized for building the steganography;such as LSB (Least Significant Bits), Discrete Cosine Transform (DCT), Discrete Fourier Transform, Spread-Spectrum Encoding, and Perceptual Masking, but all of them are challenged by steganalysis. This paper proposes a new technique for Gray Scale Image Steganography that uses the idea of image segmentation and LSB to deal with such problem. The proposed method deals with different types of images by converting them to a virtual gray scale 24 bitmaps, finds out the possible segments inside image and then computes the possible areas for each segment with boundaries. Any intruder trying to find the transformed image will not be able to understand it without the correct knowledge about the transformation process. The knowledge is represented by the key of image segmentation, key of data distribution inside segment (area selection), key of mapping within each area segment, key agreement of cryptography method, key of secret message length and key of message extension. Our method is distinguishing oneself by one master key to generate the area selection key, pixels selection keys and cryptography key. Thus, the existence of secret message is hard to be detected by the steganalysis. Experiment results show that the proposed technique satisfied the main requirements of steganography;visual appearance, modification rate, capacity, undetectability, and robustness against extraction (security). Also it achieved the maximum capacity of cover image with a modification rate equals 0.04 and visual quality for stego-image comparable to cover image.展开更多
Image steganography algorithms based on deep learning are often trained using either spatial-or frequency-domain features.It is difficult for features from a single domain to comprehensively express the content of an ...Image steganography algorithms based on deep learning are often trained using either spatial-or frequency-domain features.It is difficult for features from a single domain to comprehensively express the content of an entire image,which usually leads to poor performance because steganography is commonly multi-task.To solve this problem,this paper proposes a robust image steganography algorithm based on feature score maps,called the secure and robust image steganography network(SRIS-Net).First,instead of spatial-domain steganography,our proposed algorithm utilizes a convolutional neural network to obtain shallow spatial-domain features.These features are decomposed by Laplacian pyramid frequency-domain decomposition(LPFDD)to hide secret information in the different frequency sub-bands with a progressive assisted hiding strategy that significantly reduces the influence of the secret information on the cover image,achieving significant invisibility and robust performance.In addition,we propose a global–local embedding module(GLEM)to achieve embedding by considering the overall structure of the image and the local details,and a dual multi-scale aggregation sub-network(DMSubNet)to perform multi-scale reconstruction to improve the quality of the carrier image.For security,we propose a dual-task discriminator structure,while giving a real/fake judgment of the image,which can generate a feature score map of the cover image’s region of interest(ROI)to guide the embedding module to generate a carrier image with higher imperceptibility and undetectability.Experimental results on BOSSBase show that our SRIS-Net outperforms mainstream methods in terms of undetectability and robustness,with more than 9.2 and 3.4 dB improvement in visual quality,respectively,and the capacity can be increased up to approximately 72–96 bits per pixel.展开更多
In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independ...In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independent image different from the secret image.The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image.Thus,we only need to transmit the meaning-normal image which is not related to the secret image,and we can achieve the same effect as the transmission of the secret image.This is the first time to propose the coverless image information steganographic scheme based on generative model,compared with the traditional image steganography.The transmitted image is not embedded with any information of the secret image in this method,therefore,can effectively resist steganalysis tools.Experimental results show that our scheme has high capacity,security and reliability.展开更多
An optical image encryption system with adaptive steganography using red, green, and blue （RGB） channel integration is proposed. The optical image encryption system employs a double random phase encoding algorithm t...An optical image encryption system with adaptive steganography using red, green, and blue （RGB） channel integration is proposed. The optical image encryption system employs a double random phase encoding algorithm to encrypt and decrypt color images. The RGB channel in a color image is first integrated into a large grayscale image. Then the integrated image is encrypted by two random phase masks. The secret data is then embedded into the encrypted image with a specific hiding sequence generated by the zero-LSB （least significant bits） sorting technique which is a content-dependent and low distortion data embedding method. Experimental results show that the proposed, method has a good performance in both hiding capacity and decrypted image quality.展开更多
Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography...Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography,and watermarking.Image stenography and encryption are commonly used models to achieve improved security.Besides,optimal pixel selection process(OPSP)acts as a vital role in the encryption process.With this motivation,this study designs a new competitive swarmoptimization with encryption based stenographic technique for digital image security,named CSOES-DIS technique.The proposed CSOES-DIS model aims to encrypt the secret image prior to the embedding process.In addition,the CSOES-DIS model applies a double chaotic digital image encryption(DCDIE)technique to encrypt the secret image,and then embedding method was implemented.Also,the OPSP can be carried out by the design of CSO algorithm and thereby increases the secrecy level.In order to portray the enhanced outcomes of the CSOES-DIS model,a comparative examination with recent methods is performed and the results reported the betterment of the CSOES-DIS model based on different measures.展开更多
Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data.This property makes it difficult for steganalysts’powerful data extrac...Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data.This property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation.However,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations.In addition,these numbers may cluster in certain ranges.The hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can detect.Therefore,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego image.This paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data concealment.The AVL tree algorithm provides several advantages for image steganography.Firstly,it ensures balanced tree structures,which leads to efficient data retrieval and insertion operations.Secondly,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image quality.The data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel extraction.The green channel serves as the foundation for building a balanced binary tree.First,the sender identifies the colored cover image and secret data.The sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated information.The next step is to create a balanced binary tree based on the green channel.Utilizing the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue channel.The first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret data.After embedding the bits in the binary tree level by level,the model restores the AVL tree to create the stego image.Ultimately,the receiver receives this stego image through the public channel,enabling secret data recovery without stego or crypto keys.This method ensures that the stego image appears unsuspicious to potential attackers.Without an extraction algorithm,a third party cannot extract the original secret information from an intercepted stego image.Experimental results showed high levels of imperceptibility and security.展开更多
Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission.Currently,the main multiple images steganography algorithms main...Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission.Currently,the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible inmultiple cover images to improve the detection error rate of stego images.In order to enable the payloads to be accurately and efficiently distributed in each cover image,this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution.Firstly,the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the time required in the process of payloads distribution.Then,by reducing the difference between the features of the cover images and the stego images to increase the detection error rate of the stego images.Secondly,this paper uses a data decomposition mechanism based on Vandermonde matrix.Even if part of the data is lost during the transmission of the secret messages,as long as the data loss rate is less than the data redundancy rate,the original secret messages can be recovered.Experimental results show that the method proposed in this paper improves the efficiency of payloads distribution compared with existing multiple images steganography.At the same time,the algorithm can achieve the optimal payload distribution of multiple images steganography to improve the anti-statistical detection performance of stego images.展开更多
文摘Steganography,the art of concealing information within innocuous mediums,has been practiced for centuries and continues to evolve with advances in digital technology.In the modern era,steganography has become an essential complementary tool to cryptography,offering an additional layer of security,stealth,and deniability in digital communications.With the rise of cyber threats such as hacking,malware,and phishing,it is crucial to adopt methods that protect the confidentiality and integrity of data.This review focuses specifically on text-in-image steganography,exploring a range of techniques,including Least Significant Bit(LSB),Pixel Value Differencing(PVD),and Transform Domain methods,to evaluate their effectiveness in real-world applications.The analysis covers key parameters such as embedding capacity,computational complexity,and the interplay with data compression and cryptographic techniques.While significant progress has been made in improving the security and quality of images in steganographic systems,challenges remain.For instance,higher payloads can lead to reduced Peak Signal-to-NoiseRatio(PSNR),compromising image quality.Despite these limitations,recent advancements show promising results in balancing security with minimal distortion.This paper provides valuable insights into the strengths and weaknesses of current techniques,highlighting future research directions that may enhance both the robustness and efficiency of steganographic methods in digital security.
基金supported in part by the National Natural Science Foundation of China under Grants 62102450,62272478 and the Independent Research Project of a Certain Unit under Grant ZZKY20243127。
文摘Traditional steganography conceals information by modifying cover data,but steganalysis tools easily detect such alterations.While deep learning-based steganography often involves high training costs and complex deployment.Diffusion model-based methods face security vulnerabilities,particularly due to potential information leakage during generation.We propose a fixed neural network image steganography framework based on secure diffu-sion models to address these challenges.Unlike conventional approaches,our method minimizes cover modifications through neural network optimization,achieving superior steganographic performance in human visual perception and computer vision analyses.The cover images are generated in an anime style using state-of-the-art diffusion models,ensuring the transmitted images appear more natural.This study introduces fixed neural network technology that allows senders to transmit only minimal critical information alongside stego-images.Recipients can accurately reconstruct secret images using this compact data,significantly reducing transmission overhead compared to conventional deep steganography.Furthermore,our framework innovatively integrates ElGamal,a cryptographic algorithm,to protect critical information during transmission,enhancing overall system security and ensuring end-to-end information protection.This dual optimization of payload reduction and cryptographic reinforcement establishes a new paradigm for secure and efficient image steganography.
基金Dr.Arshiya Sajid Ansari would like to thank the Deanship of Scientific Research at Majmaah University for supporting this work under Project No.R-2023-910.
文摘Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation systems.VANETs steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection.This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss.According to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network conditions.In this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and filtering.This study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.
文摘The rapid development of data communication in modern era demands secure exchange of information. Steganography is an established method for hiding secret data from an unauthorized access into a cover object in such a way that it is invisible to human eyes. The cover object can be image, text, audio,or video. This paper proposes a secure steganography algorithm that hides a bitstream of the secret text into the least significant bits（LSBs） of the approximation coefficients of the integer wavelet transform（IWT） of grayscale images as well as each component of color images to form stego-images. The embedding and extracting phases of the proposed steganography algorithms are performed using the MATLAB software. Invisibility, payload capacity, and security in terms of peak signal to noise ratio（PSNR） and robustness are the key challenges to steganography. The statistical distortion between the cover images and the stego-images is measured by using the mean square error（MSE） and the PSNR, while the degree of closeness between them is evaluated using the normalized cross correlation（NCC）. The experimental results show that, the proposed algorithms can hide the secret text with a large payload capacity with a high level of security and a higher invisibility. Furthermore, the proposed technique is computationally efficient and better results for both PSNR and NCC are achieved compared with the previous algorithms.
基金funded by“Taif University Researchers Supporting Project No.(TURSP-2020/160),Taif University,Taif,Saudi Arabia.”。
文摘Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels,creating the stego image.However,the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload.A coverless data hiding concept is proposed to solve this issue.Coverless does not mean that cover is not required,or the payload can be transmitted without a cover.Instead,the payload is embedded by cover generation or a secret message mapping between the cover file and the payload.In this paper,a new coverless image steganography method has been proposed based on the jigsaw puzzle image generation driven by a secret message.Firstly,the image is divided into equal rows then further divided into equal columns,creating blocks(i.e.,sub-images).Then,according to secret message bits and a proposed mapping function,each block will have tabs/blanks to get the shape of a puzzle piece creating a fully shaped jigsaw puzzle stego-image.After that,the generated jigsaw puzzle image is sent to the receiver.Experimental results and analysis show a good performance in the hiding capacity,security,and robustness compared with existing coverless image steganography methods.
基金This research work was funded by Institution Fund projects under Grant No.(IFPRC-215-249-2020)Therefore,authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret data.Therefore,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time.Practically,AI techniques can be utilized to design image steganographic techniques in IIoT.In addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access.In order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT environment.The proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover image.In addition,the multi-level discrete wavelet transform(DWT)based transformation process takes place.Besides,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic System.At last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover image.In order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different measures.The experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.
基金This research is supported by the Higher Education Commission(HEC),Pakistan through its initiative of National Center for Cyber Security for the affiliated Security Testing-Innovative Secured Systems Lab(ISSL)established at University of Engineering&Technology(UET)Peshawar,Grant No.2(1078)/HEC/M&E/2018/707.
文摘Steganography aims to hide the messages from unauthorized persons for various purposes,e.g.,military correspondence,financial transaction data.Securing the data during transmission is of utmost importance these days.The confidentiality,integrity,and availability of the data are at risk because of the emerging technologies and complexity in software applications,and therefore,there is a need to secure such systems and data.There are various methodologies to deal with security issues when utilizing an open system like the Internet.This research proposes a new technique in steganography within RGB shading space to achieve enhanced security compared with existing systems.We evaluate our approach with the help of diverse image quality evaluation techniques including MSE(Mean Square Error),RMSE(Root Mean Square Error),PSNR(Peak Signal-to-Noise Ratio),MAE(Mean Absolute Error),NCC(Normalized Cross-Correlation)and SSIM(Structural Similarity Index).Our experimental results demonstrate improved strength,intangibility,and security when contrasted with existing techniques and vindicate the effectiveness of this exploration work.The proposed approach achieved a 3.6701%average higher score for PSNR Correlation than the next best existing approach.Moreover,in PSNR with a variable amount of cipher embedded in the same images of the same dimensions,the proposed approach attained a 5.22%better score.Embedding the same size of cipher in images of different size resulted a 3.56%better score.
文摘Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.
基金This work was supported by the National Natural Science Foundation of China(No.61379151,61401512,61572052,U1636219)the National Key Research and Development Program of China(No.2016YFB0801303,2016QY01W0105)the Key Technologies Research and Development Program of Henan Provinces(No.162102210032).
文摘In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection.For the spatial image,this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain.Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography,and use the minimum distortion coding to realize the embedding of the secret messages.Finally,according to the embedding modification amplitude of secret messages in the new embedded domain,the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain.The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation,the bilinear interpolation and the bicubic interpolation.And the average correct extraction rate of embedded messages increases from 50%to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method,compared with the classical steganography algorithm S-UNIWARD.Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.
基金This work was supported by Taif university Researchers Supporting Project Number(TURSP-2020/114),Taif University,Taif,Saudi Arabia.
文摘Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system.This paper presents an image scrambling method that is very useful for grayscale secret images.In this method,the secret image decomposes in three parts based on the pixel’s threshold value.The division of the color image into three parts is very easy based on the color channel but in the grayscale image,it is difficult to implement.The proposed image scrambling method is implemented in image steganography using discrete wavelet transform(DWT),singular value decomposition(SVD),and sorting function.There is no visual difference between the stego image and the cover image.The extracted secret image is also similar to the original secret image.The proposed algorithm outcome is compared with the existed image steganography techniques.The comparative results show the strength of the proposed technique.
基金This research was funded by the Ministry of Higher Education(MOHE)through Fundamental Research Grant Scheme(FRGS)under the Grand Number FRGS/1/2020/ICT01/UK M/02/4,and University Kebangsaan Malaysia for open access publication.
文摘Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.
基金This work was supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant 17KJB520021,the PAPD fund,sponsored by Qing Lan Project.
文摘Internet brings us not only the convenience of communication but also some security risks,such as intercepting information and stealing information.Therefore,some important information needs to be hidden during communication.Steganography is the most common information hiding technology.This paper provides a literature review on digital image steganography.The existing steganography algorithms are classified into traditional algorithms and deep learning-based algorithms.Moreover,their advantages and weaknesses are pointed out.Finally,further research directions are discussed.
基金Taif University Researchers Supporting Project Number(TURSP-2020/239),Taif University,Taif,Saudi Arabia.
文摘The trend of digital information transformation has become a topic of interest.Many data are threatening;thus,protecting such data from attackers is considered an essential process.Recently,a new methodology for data concealing has been suggested by researchers called coverless steganography.Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image.This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional systems.The system uses the secret message to generate the stego image in the form of one of the Intelligence Quotient(IQ)games,the maze.Firstly,a full grid is generated with several specific rows and columns determined from the number of bits of the secret message.Then,these bits are fed to the full grid to form the maze game stego image.Finally,the generated maze game stego image is sent to the recipient.The experimental results,using the Bit Error Rate(BER),were conducted,and confirmed the strength of this system represented by a high capacity,perfect performance,robustness,and stronger hiding system compared with existing coverless steganography systems.
文摘Steganography is the art of hiding a secret message in some kind of media. The main goal is not to hide only the secret message but also the existence of communication and secure data transferring. There are a lot of methods that were utilized for building the steganography;such as LSB (Least Significant Bits), Discrete Cosine Transform (DCT), Discrete Fourier Transform, Spread-Spectrum Encoding, and Perceptual Masking, but all of them are challenged by steganalysis. This paper proposes a new technique for Gray Scale Image Steganography that uses the idea of image segmentation and LSB to deal with such problem. The proposed method deals with different types of images by converting them to a virtual gray scale 24 bitmaps, finds out the possible segments inside image and then computes the possible areas for each segment with boundaries. Any intruder trying to find the transformed image will not be able to understand it without the correct knowledge about the transformation process. The knowledge is represented by the key of image segmentation, key of data distribution inside segment (area selection), key of mapping within each area segment, key agreement of cryptography method, key of secret message length and key of message extension. Our method is distinguishing oneself by one master key to generate the area selection key, pixels selection keys and cryptography key. Thus, the existence of secret message is hard to be detected by the steganalysis. Experiment results show that the proposed technique satisfied the main requirements of steganography;visual appearance, modification rate, capacity, undetectability, and robustness against extraction (security). Also it achieved the maximum capacity of cover image with a modification rate equals 0.04 and visual quality for stego-image comparable to cover image.
基金Project supported by the National Natural Science Foundation of China(No.62062023)the Guizhou Science and Technology Plan Project(No.ZK[2021]-YB314)。
文摘Image steganography algorithms based on deep learning are often trained using either spatial-or frequency-domain features.It is difficult for features from a single domain to comprehensively express the content of an entire image,which usually leads to poor performance because steganography is commonly multi-task.To solve this problem,this paper proposes a robust image steganography algorithm based on feature score maps,called the secure and robust image steganography network(SRIS-Net).First,instead of spatial-domain steganography,our proposed algorithm utilizes a convolutional neural network to obtain shallow spatial-domain features.These features are decomposed by Laplacian pyramid frequency-domain decomposition(LPFDD)to hide secret information in the different frequency sub-bands with a progressive assisted hiding strategy that significantly reduces the influence of the secret information on the cover image,achieving significant invisibility and robust performance.In addition,we propose a global–local embedding module(GLEM)to achieve embedding by considering the overall structure of the image and the local details,and a dual multi-scale aggregation sub-network(DMSubNet)to perform multi-scale reconstruction to improve the quality of the carrier image.For security,we propose a dual-task discriminator structure,while giving a real/fake judgment of the image,which can generate a feature score map of the cover image’s region of interest(ROI)to guide the embedding module to generate a carrier image with higher imperceptibility and undetectability.Experimental results on BOSSBase show that our SRIS-Net outperforms mainstream methods in terms of undetectability and robustness,with more than 9.2 and 3.4 dB improvement in visual quality,respectively,and the capacity can be increased up to approximately 72–96 bits per pixel.
基金This paper was supported by the National Natural Science Foundation of China(No.U1204606)the Key Programs for Science and Technology Development of Henan Province(No.172102210335)Key Scientific Research Projects in Henan Universities(No.16A520058).
文摘In this paper,we propose a novel coverless image steganographic scheme based on a generative model.In our scheme,the secret image is first fed to the generative model database,to generate a meaning-normal and independent image different from the secret image.The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image.Thus,we only need to transmit the meaning-normal image which is not related to the secret image,and we can achieve the same effect as the transmission of the secret image.This is the first time to propose the coverless image information steganographic scheme based on generative model,compared with the traditional image steganography.The transmitted image is not embedded with any information of the secret image in this method,therefore,can effectively resist steganalysis tools.Experimental results show that our scheme has high capacity,security and reliability.
基金supported by the National Science Council,Taiwan under Grant No.NSC 97-2221-E-468-006
文摘An optical image encryption system with adaptive steganography using red, green, and blue （RGB） channel integration is proposed. The optical image encryption system employs a double random phase encoding algorithm to encrypt and decrypt color images. The RGB channel in a color image is first integrated into a large grayscale image. Then the integrated image is encrypted by two random phase masks. The secret data is then embedded into the encrypted image with a specific hiding sequence generated by the zero-LSB （least significant bits） sorting technique which is a content-dependent and low distortion data embedding method. Experimental results show that the proposed, method has a good performance in both hiding capacity and decrypted image quality.
基金Taif University Researchers Supporting Project Number(TURSP-2020/154),Taif University,Taif,Saudi Arabia.
文摘Digital image security is a fundamental and tedious process on shared communication channels.Several methods have been employed for accomplishing security on digital image transmission,such as encryption,steganography,and watermarking.Image stenography and encryption are commonly used models to achieve improved security.Besides,optimal pixel selection process(OPSP)acts as a vital role in the encryption process.With this motivation,this study designs a new competitive swarmoptimization with encryption based stenographic technique for digital image security,named CSOES-DIS technique.The proposed CSOES-DIS model aims to encrypt the secret image prior to the embedding process.In addition,the CSOES-DIS model applies a double chaotic digital image encryption(DCDIE)technique to encrypt the secret image,and then embedding method was implemented.Also,the OPSP can be carried out by the design of CSO algorithm and thereby increases the secrecy level.In order to portray the enhanced outcomes of the CSOES-DIS model,a comparative examination with recent methods is performed and the results reported the betterment of the CSOES-DIS model based on different measures.
文摘Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data.This property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation.However,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations.In addition,these numbers may cluster in certain ranges.The hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can detect.Therefore,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego image.This paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data concealment.The AVL tree algorithm provides several advantages for image steganography.Firstly,it ensures balanced tree structures,which leads to efficient data retrieval and insertion operations.Secondly,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image quality.The data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel extraction.The green channel serves as the foundation for building a balanced binary tree.First,the sender identifies the colored cover image and secret data.The sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated information.The next step is to create a balanced binary tree based on the green channel.Utilizing the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue channel.The first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret data.After embedding the bits in the binary tree level by level,the model restores the AVL tree to create the stego image.Ultimately,the receiver receives this stego image through the public channel,enabling secret data recovery without stego or crypto keys.This method ensures that the stego image appears unsuspicious to potential attackers.Without an extraction algorithm,a third party cannot extract the original secret information from an intercepted stego image.Experimental results showed high levels of imperceptibility and security.
基金This work was supported by the National Natural Science Foundation of China(Nos.U1736214,U1804263,U1636219,61772281,61772549,and 61872448)the National Key R&D Program of China(Nos.2016YFB0801303,2016QY01W0105)the Science and Technology Innovation Talent Project of Henan Province(No.184200510018).
文摘Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission.Currently,the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible inmultiple cover images to improve the detection error rate of stego images.In order to enable the payloads to be accurately and efficiently distributed in each cover image,this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution.Firstly,the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the time required in the process of payloads distribution.Then,by reducing the difference between the features of the cover images and the stego images to increase the detection error rate of the stego images.Secondly,this paper uses a data decomposition mechanism based on Vandermonde matrix.Even if part of the data is lost during the transmission of the secret messages,as long as the data loss rate is less than the data redundancy rate,the original secret messages can be recovered.Experimental results show that the method proposed in this paper improves the efficiency of payloads distribution compared with existing multiple images steganography.At the same time,the algorithm can achieve the optimal payload distribution of multiple images steganography to improve the anti-statistical detection performance of stego images.
